1. Field of the Invention
The present invention relates to a control method and apparatus, using a neural network model, for controlling a nonlinear controlled system such as a manipulator.
2. Description of the Related Art
A conventional method of controlling a nonlinear controlled system such as a manipulator is exemplified by a method of combining nonlinear compensation and feedback control and an inverse problem technique for obtaining a manipulated variable from a mathematical model (especially a mathematical model of dynamic characteristics) of a nonlinear controlled system. In these methods, accurate control cannot be performed if a mathematical model for a controlled system is unknown.
Several methods are proposed as a method of controlling a nonlinear controlled system using a neural network model. According to a control method using a neural network model, control can be achieved by acquiring the dynamic characteristics of a controlled system by learning a neural network model even if a mathematical model of the controlled system is unknown. A conventional control method using a neural network model, however, is feed-forward control for calculating a manipulated variable from a target controlled variable or quantity. For this reason, a shift in target controlled variable caused by a disturbance cannot be compensated.
As described above, in the conventional method of combining nonlinear compensation and feedback control and the conventional method using the inverse problem technique, accurate control cannot be performed if a mathematical model for a nonlinear controlled system is not known. Therefore, a deviation of a controlled variable caused by a disturbance cannot be compensated by the method using the neural network model.